Browsing by Author "Santos, P."
Now showing 1 - 10 of 21
Results Per Page
Sort Options
- Audit on the radiographers practice for CTPA performing in emergency departmentPublication . Miranda, Dulce; da Silva, Carlos Alberto; Mateus, B.; Almeida, Rui; Vicente, Bianca; Abrantes, António; Ribeiro, A. P.; Santos, P.; Carriço, B.ComputedTomography Pulmonary Angiography (CTPA) is a first line exam used to stratify the early risk of patients with Pulmonary embolism (PE) who is a common presentation to emergency department.The diagnosis of acute Pulmonary embolism (PE) is based on direct evidence of a thrombus in two projections, either as a filling defect or as amputation of a pulmonary arterial branch When performing CTPA, it is important for the radiographer to be aware of all aspects which can lead to an indeterminate CTPA or incorrect interpretation....
- Comparing the resolution of Bartlett and MVDR estimators for bottom parameter estimation using pressure and vector sensor short array dataPublication . Felisberto, P.; Schneiderwind, J.; Santos, P.; Rodríguez, O. C.; Jesus, S. M.This work compares the resolution of a pressure and vector sensor based conventional Bartlett estimator, with their MVDR estimator counterparts, in the context of bottom characterization with a short vertical array. Santos et al. [1]demonstrated the gain of a vector sensor array (VSA) based linear estimator (Bartlett) for generic parameter estimation. Moreover, it was shown that for bottom characterization the highest resolution of the estimates were achieved with the vertical particle velocity measurements alone. The present work highlights the gain in parameter resolution of a VSA based MVDR estimator. It is shown, that also for a MVDR estimator, the vector sensor array data improves the resolution of parameter estimation. But, it is also shown, through simulations, that for bottom parameter estimation, the pressure based MVDR estimator has higher resolution and sidelobe attenuation than the VSA based Bartlett estimator. These results were verified for experimental data acquired by a four element, 30 cm long vertical VSA in the 8–14 kHz band, during the Makai Experiment 2005 sea trial, off Kauai I., Hawaii (USA).
- Comparing the resolution of Bartlett and MVDR processors for bottom parameter estimation using pressure and vector sensor short array dataPublication . Felisberto, P.; Schneiderwind, J.; Santos, P.; Rodríguez, O. C.; Jesus, S. M.This work compares the resolution of a pressure and vector sensor based conventional Bartlett estimator, with their MVDR estimator counterparts, in the context of bottom characterization with a short vertical array. Santos et al. [1] demonstrated the gain of a vector sensor array (VSA) based linear estimator (Bartlett) for generic parameter estimation. Moreover, it was shown that for bottom characterization the highest resolution of the estimates were achieved with the vertical particle velocity measurements alone. The present work highlights the gain in parameter resolution of a VSA based MVDR estimator. It is shown, that also for a MVDR estimator, the vector sensor array data improves the resolution of parameter estimation. But, it is also shown, through simulations, that for bottom parameter estimation, the pressure based MVDR estimator has higher resolution and sidelobe attenuation than the VSA based Bartlett estimator. These results were verified for experimental data acquired by a four element, 30 cm long vertical VSA in the 8–14 kHz band, during the Makai Experiment 2005 sea trial, off Kauai I., Hawaii (USA).
- Correlation between the acoustic noise field measured in a Posidonia oceanica bed and the photosynthetic activityPublication . Felisberto, P.; Zabel, F.; Rodríguez, O. C.; Santos, P.; Jesus, S. M.; Champenois, W.; Borges, A. V.; Santos, RuiDuring the period of one week, from May 8 to 15, 2013, acoustic data was gathered at three locations over a Posidonia oceanica bed in the Bay of Revellata, Corsica. Preliminary analysis of the acoustic data shows that the environmental noise field in the band 2-7kHz was dominant during the period. The noise in this band is generally associated with wind and surface agitation. However, the noise power was not significantly correlated with wind speed. On the contrary, the diel cycle of the noise power at three locations was highly correlated with the water column concentration of O2, as measured by optodes. These measurements of environmental noise have confirmed the correlation between active acoustic signals transmitted along a seagrass meadow and the photosynthetic activity of the plants observed in a previous experiment conducted in the same area .The results suggest that acoustic noise can be used as a proxy for the photosynthetic oxygen production of a Posidonia oceanica meadow. Therefore, this work is a contribution for the development of a low cost passive acoustic system to assess the primary production of coastal ecosystems .
- Estimating bottom properties with a vector sensor array during MakaiEx 2005Publication . Santos, P.; Felisberto, P.; Jesus, S. M.Nowadays, vector sensors which measure both acoustic pressure and particle velocity begin to be available in underwater acoustic systems, normally configured as vector sensor arrays (VSA). The spatial filtering capabilities of a VSA can be used, with advantage over traditional pressure only hydrophone arrays, for estimating acoustic field directionality as well as arrival times and spectral content, which could open up the possibility for its use in bottom properties' estimation. An additional motivation for this work is to test the possibility of using high frequency probe signals (say above 2 kHz) for reducing size and cost of actual sub bottom profilers and current geoacoustic inversion methods. This work studies the bottom related structure of the VSA acquired signals, regarding the emitted signal waveform, frequency band and source-receiver geometry in order to estimate bottom properties, specially bottom reflection coefficient characteristics. Such a system was used during the Makai 2005 experiment, off Kauai I., Hawai (USA) to receive precoded signals in a broad frequency band from 8 up to 14 kHz. The agreement between the observed and the modelled acoustic data is discussed and preliminary results on the bottom reflection estimation are presented.
- Estimating bottom properties with a vector sensor array during the Makai 2005 experimentPublication . Santos, P.; Felisberto, P.; Jesus, S. M.Nowadays, vector sensors which measure both acoustic pressure and particle velocity begin to be available in underwater acoustic systems, normally configured as vector sensor arrays (VSA). The spatial filtering capabilities of a VSA can be used, with advantage over traditional pressure only hydrophone arrays, for estimating acoustic field directionality as well as arrival times and spectral content, which could open up the possibility for its use in bottom properties' estimation. An additional motivation for this work is to test the possibility of using high frequency probe signals (say above 2 kHz) for reducing size and cost of actual sub bottom profilers and current geoacoustic inversion methods. This work studies the bottom related structure of the VSA acquired signals, regarding the emitted signal waveform, frequency band and source-receiver geometry in order to estimate bottom properties, specially bottom reflection coefficient characteristics. Such a system was used during the Makai 2005 experiment, off Kauai I., Hawai (USA) to receive precoded signals in a broad frequency band from 8 up to 14 kHz. The agreement between the observed and the modelled acoustic data is discussed and preliminary results on the bottom reflection estimation are presented.
- Experimental results of geometric and geoacosutic parameter estimation using a vector sensor arrayPublication . Santos, P.; Felisberto, P.; Jesus, S. M.; João, J.The objective of this paper is to present an overview of the work developed at SiPLAB, University of Algarve, with vector sensor data collected during Makai experiment 2005, in geometric and geoacoustic parameter estimation. During this experiment devoted to high frequency initiative, acoustic data were acquired by a four element vertical vector sensor array (VSA). A vector sensor is a directional sensor constituted by one omni directional pressure sensor and three velocity-meters, where both the acoustic pressure and the three particle velocity components are measured. The spatial filtering capabilities of the vector sensors are used to estimate the direction of arrival (DOA) of low and high frequency acoustic sources considering a single and a multiple sensor VSA. An inversion method based on Bartlett estimator is used for three dimensional localization of ship’s noise where the noise source is estimated in range and depth taking into accounts the azimuth given by DOA. Moreover, this method is applied to seabed parameters estimation like sediment compressional speed, density and compressional attenuation, contributing to improve the resolution of these parameters.
- Geoacoustic matched-field inversion using a vector sensor arrayPublication . Santos, P.; Felisberto, P.; Rodríguez, O. C.; Jesus, S. M.Vector sensors measure the acoustic pressure and the particle velocity components. This type of sensor has the ability to provide information in both vertical and azimuthal direction allowing increased directivity. These characteristics have been explored by many authors and most of the studies on vector sensors found in literature are related to direction of arrival (DOA) estimation. However, assembled into an array, a Vector Sensor Array (VSA) improves spatial filtering capabilities and can be used with advantage in other applications such as geoacoustic inversion. In this paper it will be shown that a reliable estimation of ocean bottom parameters, such as sediment compressional speed, density and compressional attenuation, can be obtained using high-frequency signals and a small aperture vertical VSA. The introduction of particle velocity on matched-field processing (MFP) techniques is going to be presented. It will be seen how MFP, usually done with acoustic pressure, can be adapted in order to incorporate the three components of the particle velocity. Comparisons between several processors based either in individual particle velocity components or using all the VSA outputs, are made for simulated and experimental data. The quaternion model, which is founded on hypercomplex algebra, thus more appropriate to represent the 4 dimensional VSA data, is also presented in the MFP context. A novel ray tracing model is used to generate field replicas that include both the acoustic pressure and the particle velocity outputs. The data considered herein was acquired by a four element vertical VSA in the 8-14 kHz band, during the Makai Experiment 2005 sea trial, off Kauai I., Hawaii (USA). The results shows that, when the particle velocity is included it can significantly increase the resolution of bottom properties estimation and in some cases a similar result is obtained using only the vertical component of the particle velocity.
- Geometric and seabed parameter estimation using a vector sensor array: experimental results from Makai experiment 2005Publication . Santos, P.; Felisberto, P.; Rodríguez, O. C.; João, J.; Jesus, S. M.A vector sensor is constituted by one omni directional pressure sensor and three velocity-meters that are sensitive in a specific direction - x, y or z. Since a vector sensor is able to measure the three particle velocity directional components it acts as a spatial filter and therefore is advantageous in three dimensional direction of arrival (DOA) estimation. The potential gain obtained in DOA estimation can be extended to other geometric parameters such as source range and depth, as well as seabed parameters. The objective of this paper is to present experimental results of a four element vertical vector sensor array (VSA) data set collected during MakaiEx'05 experiment for geometric (range and depth) and seabed geoacoustic parameter estimation (sediment compressional speed, density and compressional attenuation). The parameter estimation problem is posed as an inversion method based on an extension of the conventional pressure only Bartlett estimator to particle velocity. The developed VSA based Bartlett estimator is proportional to the pressure only Bartlett estimator response by a directivity factor, providing an improved side lobe reduction or even suppression when compared with the pressure only response. This behavior will be illustrated for geometric and seabed parameters clearly showing the advantages of the use of VSA over hydrophone arrays. In source localization the VSA outperforms an array of hydrophones of same number of sensors. Moreover, when the VSA Bartlett estimator is applied for seabed parameter estimation, it will be shown that the estimation resolution of these parameters increased significantly, even for density and compressional attenuation, parameters difficult to estimate using an array of hydrophones.
- Matched field processing with a vector sensor arrayPublication . Santos, P.The main objective of this report is to present a particle velocity-pressure joint data model and a version of Bartlett estimator in order to include the particle velocity in Matched- eld inversion tecnhiques. Both data model and estimator will be used in the estimation of bottom parameters such as: the compressional wave speed, the compressional attenuation and the density of sediment, where the simulations results are pro- vided by the TRACE ray tracing model, capable for particle velocity outputs.
- «
- 1 (current)
- 2
- 3
- »